get_job_grades

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses the data scope (109 records, what fields exist, job-category breakdown), which is useful. However, it doesn't explicitly state note whether the operation is read-only, whether it supports pagination, or what the exact output shape is beyond the field list. Since an output schema exists, some of this burden is reduced, but the description could still state that it's a safe lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is tightly structured with a summary line, a data-overview line, and clearly separated parameter documentation. The Korean formatting is compact, front-loads the purpose, and every sentence earns its place. The parameter blocks are formatted simply and readably.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple lookup tool with an output schema present, the description is nearly complete. Both parameters are fully documented with default values visible in the schema, the result content is described, and the 109-item scope sets expectations. The only minor gap is that the output schema presumably covers the return shape, so nothing critical is missing. Slight deduction for not explicitly stating that the operation is non-destructive, but with an output schema and no mutation verbs in the description, this is a minor omission.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully compensates. Both parameters are documented in detail with semantics and concrete examples: grade_level is exact-match (예: 3 → 3급 전체), keyword is partial-match (예: '운전', '차량', '사무영업'). The examples make filter behavior unambiguous. This is exemplary parameter documentation with zero coverage in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear specific verb-resource pair ('직급 코드 정보 조회' - retrieve job grade code information) and lists exactly what is returned: grade level, grade name, and grade code. It also specifies the number of records (109건) and the categories covered. It doesn't explicitly differentiate from siblings, but among a list of lookup tools, its domain (job grades) is clearly its own.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the description being a lookup/retrieval tool, but there is no explicit when/when-not guidance or mention of alternatives. For a simple reference-data lookup among many sibling get_* code and department tools, the context is clear enough that an agent can infer when to call it (when grade info is needed), but it doesn't explicitly state exclusions or preferred alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.